Electrophysiological methods, including event-related potential and functional connectivity approaches, have strong potential to clarify mechanisms of substance use treatment response and characterize individual differences therein. Veterans are disproportionately affected by disorders of addiction, of which cocaine use disorder (CUD) is particularly problematic due to high relapse rates and the absence of approved pharmaco- therapy treatment options. Behavioral interventions for CUD, have therefore become an important focus of research and Contingency Management (CM) has emerged as the best-supported and most widely used approach. CM involves reinforcing cocaine abstinence (established through objective testing) with reliable, short-term reward, such as chances to win prizes (i.e., Prize-Based CM or PBCM). In response to substantial empirical support, national dissemination of PBCM has been supported by a VHA initiative since 2011. However, PBCM response rates are variable and long-term benefits are limited ? problems magnified by the cost of implementation with respect to staffing and prizes. Measurement-based approaches to PBCM implementation have strong promise to improve the effectiveness and efficiency of CM programming but have not yet been investigated within the VA or considered in relation to promising neuromarkers. Importantly, two versions of PBCM are already utilized at VA sites and may differentially benefit individuals with distinct neurocognitive profiles. Specifically, VA PBCM programs employ either abstract (voucher prize) or concrete (tangible prize) incentives, the latter of which may more effectively incentivize abstinence in Veterans with poor future-oriented thinking and planning ability. While selection between existing PBCM variants is currently driven by practical considerations (e.g., provider convenience), measurement of pretreatment neurocognitive functioning could meaningfully and realistically inform clinical decision-making in this regard. This CDA aims to advance measurement-based implementation of CM by testing a novel neurocognitive model of CM with immediate implications for the use of abstract versus concrete PBCM incentives within the VA. Specifically, the future-minded decision-making (FMDM) model posits that CM scaffolds future-oriented goal representation and self-control to support abstinence during in the moment use-related decision-making. For individuals with greater FMDM impairment, concrete, readily-accessible incentives may be more effective than abstract monetary rewards (e.g., vouchers) which require future-oriented thinking and planning to inherit value. To test this model, neurocognitive substrates of FMDM will be examined as predictors of differential treatment response in voucher (VoucherPBCM) versus tangible prize (TangiblePBCM) versions of the intervention used within the VA. Treatment-related change in neural and cognitive-behavioral correlates of FMDM will also be evaluated in PBCM relative to treatment-as-usual (TAU) care. A total of 180 Veterans with CUD will be allocated to VoucherPBCM (n=70), TangiblePBCM (n=70), or TAU (n=40) conditions and followed for a 12 week treatment interval. Pre- and post-treatment electroencephalography (EEG) and cognitive-behavioral assessments will be used to measure FMDM-related constructs (working memory, self- control, future-oriented decision-making, future reward representation) and related neuromarkers. These measures will subsequently be investigated as predictors of differential treatment response in VoucherPBCM versus Tangible PBCM. Longitudinal change in FMDM-related neural substrates and cognitive abilities will also be evaluated for evidence of neuroadaptation (e.g., changes in functional connectivity) and enhancement of FMDM function through PBCM. The proposed research will be supported by focused training in the areas of (1) predictive analytics, (2) functional connectivity analysis of EEG data, (3) longitudinal evaluation of neuroadaptive mechanisms, and (4) clinical trials research. Together, research and training aims will support development of an independent program of research targeting precision implementation of CM within the VA.